Prelert Anomaly Detective API Engine Beta

Get fast, accurate anomaly detection across any data source with Prelert’s behavioral analytics platform
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Behavioral analytics for IT security and operations teams

Prelert’s behavioral analytics platform analyzes log data from a variety of data stores, finds anomalies that can indicate advanced cyber threats and IT performance problems. Using machine learning anomaly detection, Prelert offers:

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img-real-problems-01Early Detection of Incidents

Detect advanced threat activity such as data exfiltration and command and control communication in near real-time. Identify IT operations problems before users report them.

img-real-problems-02Faster Root Cause Discovery

Find the root cause of anomalies faster. Get the full story behind cyberthreats and IT ops issues with algorithms that learn minute-to-minute what is normal for your environment.  Involve fewer people in triage and get answers fast.

img-real-problems-03Reduced False Positives

Because Prelert’s analytics run on log data from a broad set of sources, they are able to consider more context than monitoring tools that rely on a single source.  This additional context helps to significantly reduce false positives.

Anomaly Detective API Engine Beta:
Put Machine Learning to Work

The Prelert API engine helps you automate the analysis of massive data sets across a wide range of data sources, eliminating manual effort and human error. Downloaded as a software application with a REST API, Prelert analyzes your data and provides anomaly results via the REST API.

Benefits:

  • 100% unsupervised machine learning
  • Cuts through millions of data points in seconds
  • Identifies anomalous behavior patterns in near real-time
  • Ranks anomalies by probability of occurrence
  • Gives you the actionable insights you need to act quickly
  • Open REST API and Open Source UI

Works with:

  • Log management and search platforms (e.g. Elastic Stack, Sumo Logic)
  • Big Data Stores (e.g. Hadoop)
  • Hosted Big Data Stores (e.g. Google Data Store, AWS Red Shift)

Sample Use Cases

Security Analytics

  • Detect DNS Data Exfiltration (Tunneling) in DNS Query Requests
  • Detect Suspicious Network Activity (App-Port) in Firewall Logs
  • Detect Suspicious Login Activity in Endpoint Detection and Response Logs
      View more

IT Operations Insights

  • Analyze Operational Metrics
  • Discover Root Cause
  • Track Business KPIs

Retail Order Analytics

  • Detect Revenue-Impacting Events
  • Accurately Model Periodic Behaviors
  • Find Operational, Process-Related, or Externally-Created Issues

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